scholarly journals Systematical Analysis of the Protein Targets of Lactoferricin B and Histatin-5 Using Yeast Proteome Microarrays

2019 ◽  
Vol 20 (17) ◽  
pp. 4218 ◽  
Author(s):  
Pramod Shah ◽  
Wei-Sheng Wu ◽  
Chien-Sheng Chen
Keyword(s):  
Protein Complex ◽  
Synthetic Lethality ◽  
Enrichment Analysis ◽  
Growth Inhibition Assay ◽  
Protein Targets ◽  
Histatin 5 ◽  
Synthetic Lethal ◽  
Yeast Proteome ◽  
Lower Minimum Inhibitory Concentration ◽  
Cellular Components

Antimicrobial peptides (AMPs) have potential antifungal activities; however, their intracellular protein targets are poorly reported. Proteome microarray is an effective tool with high-throughput and rapid platform that systematically identifies the protein targets. In this study, we have used yeast proteome microarrays for systematical identification of the yeast protein targets of Lactoferricin B (Lfcin B) and Histatin-5. A total of 140 and 137 protein targets were identified from the triplicate yeast proteome microarray assays for Lfcin B and Histatin-5, respectively. The Gene Ontology (GO) enrichment analysis showed that Lfcin B targeted more enrichment categories than Histatin-5 did in all GO biological processes, molecular functions, and cellular components. This might be one of the reasons that Lfcin B has a lower minimum inhibitory concentration (MIC) than Histatin-5. Moreover, pairwise essential proteins that have lethal effects on yeast were analyzed through synthetic lethality. A total of 11 synthetic lethal pairs were identified within the protein targets of Lfcin B. However, only three synthetic lethal pairs were identified within the protein targets of Histatin-5. The higher number of synthetic lethal pairs identified within the protein targets of Lfcin B might also be the reason for Lfcin B to have lower MIC than Histatin-5. Furthermore, two synthetic lethal pairs were identified between the unique protein targets of Lfcin B and Histatin-5. Both the identified synthetic lethal pairs proteins are part of the Spt-Ada-Gcn5 acetyltransferase (SAGA) protein complex that regulates gene expression via histone modification. Identification of synthetic lethal pairs between Lfcin B and Histatin-5 and their involvement in the same protein complex indicated synergistic combination between Lfcin B and Histatin-5. This hypothesis was experimentally confirmed by growth inhibition assay.

scholarly journals SynLethDB 2.0: A web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery

2021 ◽  
Author(s):  
Jie Wang ◽  
Min Wu ◽  
Xuhui Huang ◽  
Li Wang ◽  
Sophia Zhang ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Knowledge Graph ◽  
Lethal Gene ◽  
Web Interface ◽  
Dynamic Graph ◽  
Web Based ◽  
Synthetic Lethal ◽  
Graph Viewer

Two genes are synthetic lethal if mutations in both genes result in impaired cell viability, while mutation of either gene does not affect the cell survival. The potential usage of synthetic lethality (SL) in anticancer therapeutics has attracted many researchers to identify synthetic lethal gene pairs. To include newly identified SLs and more related knowledge, we present a new version of the SynLethDB database to facilitate the discovery of clinically relevant SLs. We extended the first version of SynLethDB database significantly by including new SLs identified through CRISPR screening, a knowledge graph about human SLs, and new web interface, etc. Over 16,000 new SLs and 26 types of other relationships have been added, encompassing relationships among 14,100 genes, 53 cancers, and 1,898 drugs, etc. Moreover, a brand-new web interface has been developed to include modules such as SL query by disease or compound, SL partner gene set enrichment analysis and knowledge graph browsing through a dynamic graph viewer. The data can be downloaded directly from the website or through the RESTful APIs. The database is accessible online at http://synlethdb.sist.shanghaitech.edu.cn/v2.

scholarly journals Using Yeast Synthetic Lethality To Inform Drug Combination for Malaria

2018 ◽  
Vol 62 (4) ◽  
Author(s):  
Suvitha Subramaniam ◽  
Christoph D. Schmid ◽  
Xue Li Guan ◽  
Pascal Mäser
Keyword(s):  
Plasmodium Falciparum ◽  
Drug Combination ◽  
Synthetic Lethality ◽  
Drug Combinations ◽  
Synthetic Lethal Interaction ◽  
Content Type ◽  
Synthetic Lethal ◽  
Gene Pairs ◽  
Phosphatidylinositol 4

ABSTRACT Combinatorial chemotherapy is necessary for the treatment of malaria. However, finding a suitable partner drug for a new candidate is challenging. Here we develop an algorithm that identifies all of the gene pairs of Plasmodium falciparum that possess orthologues in yeast that have a synthetic lethal interaction but are absent in humans. This suggests new options for drug combinations, particularly for inhibitors of targets such as P. falciparum calcineurin, cation ATPase 4, or phosphatidylinositol 4-kinase.

A Screen for Dynein Synthetic Lethals in Aspergillus nidulans Identifies Spindle Assembly Checkpoint Genes and Other Genes Involved in Mitosis

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 101-116
Author(s):  
Vladimir P Efimov ◽  
N Ronald Morris
Keyword(s):  
Aspergillus Nidulans ◽  
Spindle Assembly Checkpoint ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Spindle Assembly ◽  
Nuclear Migration ◽  
Cytoplasmic Dynein ◽  
Vesicle Transport ◽  
Synthetic Lethal ◽  
Checkpoint Genes

Abstract Cytoplasmic dynein is a ubiquitously expressed microtubule motor involved in vesicle transport, mitosis, nuclear migration, and spindle orientation. In the filamentous fungus Aspergillus nidulans, inactivation of cytoplasmic dynein, although not lethal, severely impairs nuclear migration. The role of dynein in mitosis and vesicle transport in this organism is unclear. To investigate the complete range of dynein function in A. nidulans, we searched for synthetic lethal mutations that significantly reduced growth in the absence of dynein but had little effect on their own. We isolated 19 sld (synthetic lethality without dynein) mutations in nine different genes. Mutations in two genes exacerbate the nuclear migration defect seen in the absence of dynein. Mutations in six other genes, including sldA and sldB, show a strong synthetic lethal interaction with a mutation in the mitotic kinesin bimC and, thus, are likely to play a role in mitosis. Mutations in sldA and sldB also confer hypersensitivity to the microtubule-destabilizing drug benomyl. sldA and sldB were cloned by complementation of their mutant phenotypes using an A. nidulans autonomously replicating vector. Sequencing revealed homology to the spindle assembly checkpoint genes BUB1 and BUB3 from Saccharomyces cerevisiae. Genetic interaction between dynein and spindle assembly checkpoint genes, as well as other mitotic genes, indicates that A. nidulans dynein plays a role in mitosis. We suggest a model for dynein motor action in A. nidulans that can explain dynein involvement in both mitosis and nuclear distribution.

scholarly journals Cohesin mutations are synthetic lethal with stimulation of WNT signaling

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Chue Vin Chin ◽  
Jisha Antony ◽  
Sarada Ketharnathan ◽  
Anastasia Labudina ◽  
Gregory Gimenez ◽  
...  
Keyword(s):  
Wnt Signaling ◽  
Therapeutic Strategy ◽  
Synthetic Lethality ◽  
Mcf10a Cell ◽  
Synthetic Lethal ◽  
Deletion Mutations ◽  
Damage Repair ◽  
Genes Encoding ◽  
Mutant Cells ◽  
Gsk3 Inhibitor

Mutations in genes encoding subunits of the cohesin complex are common in several cancers, but may also expose druggable vulnerabilities. We generated isogenic MCF10A cell lines with deletion mutations of genes encoding cohesin subunits SMC3, RAD21, and STAG2 and screened for synthetic lethality with 3009 FDA-approved compounds. The screen identified several compounds that interfere with transcription, DNA damage repair and the cell cycle. Unexpectedly, one of the top ‘hits’ was a GSK3 inhibitor, an agonist of Wnt signaling. We show that sensitivity to GSK3 inhibition is likely due to stabilization of β-catenin in cohesin-mutant cells, and that Wnt-responsive gene expression is highly sensitized in STAG2-mutant CMK leukemia cells. Moreover, Wnt activity is enhanced in zebrafish mutant for cohesin subunits stag2b and rad21. Our results suggest that cohesin mutations could progress oncogenesis by enhancing Wnt signaling, and that targeting the Wnt pathway may represent a novel therapeutic strategy for cohesin-mutant cancers.

scholarly journals A network-based approach to integrate nutrient environment in the prediction of synthetic lethality in cancer metabolism

2021 ◽  
Author(s):  
Iñigo Apaolaza ◽  
Edurne San José-Enériz ◽  
Luis Valcarcel ◽  
Xabier Agirre ◽  
Felipe Prosper ◽  
...  
Keyword(s):  
Cancer Metabolism ◽  
Synthetic Lethality ◽  
Experimental Proof ◽  
Synthetic Lethal ◽  
New Family ◽  
Novel Approach ◽  
Synthetic Lethal Interactions ◽  
Nutrient Environment ◽  
Tumor Environment ◽  
Definition Of

Synthetic Lethality (SL) is a promising concept in cancer research. A number of computational methods have been developed to predict SL in cancer metabolism, among which our network-based computational approach, based on genetic Minimal Cut Sets (gMCSs), can be found. A major challenge of these approaches to SL is to systematically consider tumor environment, which is particularly relevant in cancer metabolism. Here, we propose a novel definition of SL for cancer metabolism that integrates genetic interactions and nutrient availability in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase inhibition in different environments. Finally, our novel approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.

scholarly journals Cohesin mutations are synthetic lethal with stimulation of WNT signaling

2020 ◽  
Author(s):  
Chue Vin Chin ◽  
Jisha Antony ◽  
Sarada Ketharnathan ◽  
Gregory Gimenez ◽  
Kate M. Parsons ◽  
...  
Keyword(s):  
Wnt Signaling ◽  
Synthetic Lethality ◽  
Mcf10a Cell ◽  
Synthetic Lethal ◽  
Deletion Mutations ◽  
Damage Repair ◽  
Genes Encoding ◽  
Cohesin Subunit ◽  
Mutant Cells ◽  
Gsk3 Inhibitor

AbstractMutations in genes encoding subunits of the cohesin complex are common in several cancers, but may also expose druggable vulnerabilities. We generated isogenic MCF10A cell lines with deletion mutations of genes encoding cohesin subunits SMC3, RAD21 and STAG2 and screened for synthetic lethality with 3,009 FDA-approved compounds. The screen identified several compounds that interfere with transcription, DNA damage repair and the cell cycle. Unexpectedly, one of the top ‘hits’ was a GSK3 inhibitor, an agonist of Wnt signaling. We show that sensitivity to GSK3 inhibition is likely due to stabilization of β-catenin in cohesin mutant cells, and that Wnt-responsive gene expression is highly sensitized in STAG2-mutant CMK leukemia cells. Moreover, Wnt activity is enhanced in zebrafish mutant for cohesin subunit rad21. Our results suggest that cohesin mutations could progress oncogenesis by enhancing Wnt signaling, and that targeting the Wnt pathway may represent a novel therapeutic strategy for cohesin mutant cancers.

Synthetic Lethality: From Research to Precision Cancer Nanomedicine

2018 ◽  
Vol 18 (4) ◽  
pp. 337-346 ◽  
Author(s):  
Anuradha Gupta ◽  
Anas Ahmad ◽  
Aqib Iqbal Dar ◽  
Rehan Khan
Keyword(s):  
Cancer Cell ◽  
Mutational Analysis ◽  
Synthetic Lethality ◽  
Therapeutic Index ◽  
Genetic Alterations ◽  
Cancer Drug ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Therapeutic Molecules ◽  
Drug Resistant Phenotype

Cancer is an evolutionary disease with multiple genetic alterations, accumulated due to chromosomal instability and/or aneuploidy and it sometimes acquires drug-resistant phenotype also. Whole genome sequencing and mutational analysis helped in understanding the differences among persons for predisposition of a disease and its treatment non-responsiveness. Thus, molecular targeted therapies came into existence. Among them, the concept of synthetic lethality have enthralled great attention as it is a pragmatic approach towards exploiting cancer cell specific mutations to specifically kill cancer cells without affecting normal cells and thus enhancing anti-cancer drug therapeutic index. Thus, this approach helped in discovering new therapeutic molecules for development of precision medicine. Nanotechnology helped in delivering these molecules to the target site in an effective concentration thus reducing off target effects of drugs, dose and dosage frequency drugs. Researchers have tried to deliver siRNA targeting synthetic lethal partner for target cancer cell killing by incorporating it in nanoparticles and it has shown efficacy by preventing tumor progression. This review summarizes the brief introduction of synthetic lethality, and synthetic lethal gene interactions, with a major focus on its therapeutic anticancer potential with the application of nanotechnology for development of personalized medicine.

scholarly journals Geldanamycin-Derived HSP90 Inhibitors Are Synthetic Lethal with NRF2

2020 ◽  
Vol 40 (22) ◽  
Author(s):  
Liam Baird ◽  
Takafumi Suzuki ◽  
Yushi Takahashi ◽  
Eiji Hishinuma ◽  
Daisuke Saigusa ◽  
...  
Keyword(s):  
Target Genes ◽  
Synthetic Lethality ◽  
Drug Repositioning ◽  
Lethal Effect ◽  
Cancer Therapies ◽  
Dependent Manner ◽  
Hsp90 Inhibitors ◽  
Synthetic Lethal ◽  
Activating Mutations ◽  
Approved Drugs

ABSTRACT Activating mutations in KEAP1-NRF2 are frequently found in tumors of the lung, esophagus, and liver, where they are associated with aggressive growth, resistance to cancer therapies, and low overall survival. Despite the fact that NRF2 is a validated driver of tumorigenesis and chemotherapeutic resistance, there are currently no approved drugs which can inhibit its activity. Therefore, there is an urgent clinical need to identify NRF2-selective cancer therapies. To this end, we developed a novel synthetic lethal assay, based on fluorescently labeled isogenic wild-type and Keap1 knockout cell lines, in order to screen for compounds which selectively kill cells in an NRF2-dependent manner. Through this approach, we identified three compounds based on the geldanamycin scaffold which display synthetic lethality with NRF2. Mechanistically, we show that products of NRF2 target genes metabolize the quinone-containing geldanamycin compounds into more potent HSP90 inhibitors, which enhances their cytotoxicity while simultaneously restricting the synthetic lethal effect to cells with aberrant NRF2 activity. As all three of the geldanamycin-derived compounds have been used in clinical trials, they represent ideal candidates for drug repositioning to target the currently untreatable NRF2 activity in cancer.

scholarly journals SL-BioDP: Multi-Cancer Interactive Tool for Prediction of Synthetic Lethality and Response to Cancer Treatment

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1682 ◽  
Author(s):  
Xiang Deng ◽  
Shaoli Das ◽  
Kristin Valdez ◽  
Kevin Camphausen ◽  
Uma Shankavaram
Keyword(s):  
Clinical Relevance ◽  
Synthetic Lethality ◽  
Drug Efficacy ◽  
Synthetic Lethal ◽  
Cancer Data ◽  
Cancer Pathways ◽  
Kaplan Meier ◽  
Survival Pathways ◽  
Synthetic Lethal Interactions ◽  
Cancer Genome Atlas

Synthetic lethality exploits the phenomenon that a mutation in a cancer gene is often associated with new vulnerability which can be uniquely targeted therapeutically, leading to a significant increase in favorable outcome. DNA damage and survival pathways are among the most commonly mutated networks in human cancers. Recent data suggest that synthetic lethal interactions between a tumor defect and a DNA repair pathway can be used to preferentially kill tumor cells. We recently published a method, DiscoverSL, using multi-omic cancer data, that can predict synthetic lethal interactions of potential clinical relevance. Here, we apply the generality of our models in a comprehensive web tool called Synthetic Lethality Bio Discovery Portal (SL-BioDP) and extend the cancer types to 18 cancer genome atlas cohorts. SL-BioDP enables a data-driven computational approach to predict synthetic lethal interactions from hallmark cancer pathways by mining cancer’s genomic and chemical interactions. Our tool provides queries and visualizations for exploring potentially targetable synthetic lethal interactions, shows Kaplan–Meier plots of clinical relevance, and provides in silico validation using short hairpin RNA (shRNA) and drug efficacy data. Our method would thus shed light on mechanisms of synthetic lethal interactions and lead to the discovery of novel anticancer drugs.

scholarly journals Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization

2019 ◽  
Vol 20 (S19) ◽  
Author(s):  
Jiang Huang ◽  
Min Wu ◽  
Fan Lu ◽  
Le Ou-Yang ◽  
Zexuan Zhu
Keyword(s):  
Matrix Factorization ◽  
Drug Targets ◽  
Synthetic Lethality ◽  
Cancer Therapeutics ◽  
The Self ◽  
Interaction Data ◽  
Synthetic Lethal Interaction ◽  
Synthetic Lethal ◽  
Interaction Prediction ◽  
Synthetic Lethal Interactions

Abstract Background Synthetic lethality has attracted a lot of attentions in cancer therapeutics due to its utility in identifying new anticancer drug targets. Identifying synthetic lethal (SL) interactions is the key step towards the exploration of synthetic lethality in cancer treatment. However, biological experiments are faced with many challenges when identifying synthetic lethal interactions. Thus, it is necessary to develop computational methods which could serve as useful complements to biological experiments. Results In this paper, we propose a novel graph regularized self-representative matrix factorization (GRSMF) algorithm for synthetic lethal interaction prediction. GRSMF first learns the self-representations from the known SL interactions and further integrates the functional similarities among genes derived from Gene Ontology (GO). It can then effectively predict potential SL interactions by leveraging the information provided by known SL interactions and functional annotations of genes. Extensive experiments on the synthetic lethal interaction data downloaded from SynLethDB database demonstrate the superiority of our GRSMF in predicting potential synthetic lethal interactions, compared with other competing methods. Moreover, case studies of novel interactions are conducted in this paper for further evaluating the effectiveness of GRSMF in synthetic lethal interaction prediction. Conclusions In this paper, we demonstrate that by adaptively exploiting the self-representation of original SL interaction data, and utilizing functional similarities among genes to enhance the learning of self-representation matrix, our GRSMF could predict potential SL interactions more accurately than other state-of-the-art SL interaction prediction methods.

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